Computational fluid dynamics driven mass transfer model for the prediction of CO2 corrosion in pipelines

Abstract

A novel, computational fluid dynamics (CFD) driven modelling methodology for predicting $C{O}_2$ corrosion rates in pipelines is presented. CFD is used to provide accurate predictions of the viscous sublayer thickness and turbulent diffusivities, which are then used within a mass transfer model of aqueous $C{O}_2$ corrosion. Comparisons with experimental measurements of corrosion rate in horizontal pipe flow and corresponding theoretical predictions, based on empirical correlations and previous CFD approaches, show the new approach is more accurate for flows in the range of pH 4 to 6. However, the key advantage of the new approach is its flexibility. Existing models are inaccurate and highly restrictive, having been derived for very simple cases, such as 1 D pipe flow. In contrast, the new methodology provides a firm, scientific foundation for predicting corrosion rates by determining conditions in the viscous sublayer in much more complex, and practically relevant, flow situations.